Online identity theft, financial information theft, phishing, viruses, spyware, and other data communication-related malicious activities cost businesses, individuals, academic institutions, and governments billions of dollars each year. Further, such activities are also responsible for significant lost productivity, nuisance, and may inhibit use of online communication. Such activities plague not only users of commercial servers, but are also a major concern for users of other networks and systems including government computer systems, banking computer systems and online banking platforms, academic computer systems, and online retail platforms.
Various methods and systems have been proposed for user identification, authentication, and prevention of attacks and phishing schemes in the context of network data communication. These known techniques are typically based on a small number of simple mechanisms that have proven to be inadequate against sophisticated malicious and/or criminal activities. Further, these known techniques are incapable of adapting to advancements in the technology and skill of malicious entities, who have demonstrated an ability to rapidly adjust their techniques and methods.
Accordingly, a need exists for robust and adaptive systems and methods for detecting many forms of data-communication, phishing, and security-related threats, and for reacting to such detection by deactivating the detected threats and/or correcting their effects.